I guess the views of Penn, Tesfatsion and Markovsky (excerpted below)
expressed in the simulation and explanation (now theory) thread are
fairly typical and widespread.  They are consistent with conventional
approaches to social science.  Theory predominates over observation.  I
have been arguing (e.g. in my Presidential Address to ESSA) that if
social simulation with agents is to be anything other than another in
the long line of failed approaches to social science, it will be a
positive departure only because it facilitates the dominance of
observation over theory.

The great successful scientists -- Copernicus, Kepler, Galileo, Newton,
Darwin, Planck, Faraday, Einstein, Watson & Crick (maybe not quite in
the class of the others) -- built their conceptual structures and
generalisations around observation.  Theory always gave way to
evidence.  Newton and Darwin in particular kept their theories to
themselves for decades before being convinced that they were supported
by a sufficuently wide range of evidence.  Only when these theoretical
structures were well validated did they come into general use for
guiding new observation, identifying new problems and, to solve those
problems, developing new theoretical structures based on and validated
by new evidence.

Consider this tradition in relation to the following excerpts:


Alan Penn:

> can anyone think of excellent examples of
> simulation providing explanation in any field (let alone sociology).
> It seems to me that simulations (at their best) are built on top of
> pre-existing explanatory theory, they may act as tests of those
> theories, but in a true Popperian sense, can do little to confirm only
> perhaps help falsify them.



If you start from a social theory that does not itself specify agent
behaviour and interaction so that those specifications can be validated
by, for example, the individuals the agents represent, then the only
link with evidence is the predictions generated by the theory.  If there
are no correct predictions, then there is no link at all between theory
and the world we observe.  There has never in the history of Economics
and Management Science been a correct forecast of macroeconomic or
financial market turning points or turning points in retail market sales
(by brand or SKU).  I know less about sociology, but my reading of the
journals in that field suggests that no sociological theory offers
systematically well validated predictions, either.  Presumably, top-down
sociological theory does not offer well validated propositions about
individuals and their interactions.  Does anyone have any
counterexamples to these statements?

Leigh Tesfatsion (paper cited in her email):

   Thus, as implemented for this study, the labor market framework
comprises an
    equal number of work suppliers and employers. These work suppliers
and employers
    repeatedly participate in costly searches for worksite partners on
the basis of
   continually updated expected utility, engage in efficiency-wage
worksite interactions
   modelled as prisoner's dilemma games, and evolve their worksite
strategies over time
   on the basis of the earnings secured by these strategies in past
worksite interactions.

This excerpt from Leigh's paper is perhaps a case in point.  I would be
astonished if anyone could provide evidence that employers and employees
(== work suppliers, presumably) would claim to "participate in costly
searches for worksite partners on the basis of continually updated
expected utility."  Is there any independent evidence that prisoners'
dilemma games are good representations of "worksite interactions"?  This
is a pretty good example of starting from theory (which has been shown
to be invalid by experimental economists repeatedly over the past 50
years) in order to draw conclusions about the world we observe.  Why is
it better to restate the problem in terms of such a theory than to get
evidence about actual worksite behaviour and design agents to describe
that behaviour?


Barry Markovsky

>> I want to expand on Alan Penn's comments (below) because I think there
>> are some common misunderstandings and misuses of simulations in
>> sociology that we need to battle.
>>
>> Say you start with a typical discursive sociological theory, and you
>> want to write a simulation that is in some sense designed to reflect
>> the claims and explanatory mechanisms of that theory.
>

> By this view, every simulation provides an explanation: Their
> statements and functional relationships constitute the explanations
> for the
> patterns of output they generate. Certainly Sugarscape accomplishes
> this (as Mike points out below), and so do countless others. A reader may
> feel that such an explanation flawed or insufficient, but then the
> burden is on the reader either to show how the simulation fails to
> account for the phenomenon it intended to explain, or to provide an
> alternative theory or simulation that provides a superior account.


I don't understand why the burden is on the reader "either to show how
the simulation fails to account for the phenomenon it intended to
explain, or to provide an alternative theory or simulation."  An
alternative scientific approach that has worked well in the physical and
biological sciences is to place the burden on the theorist/modeller to
demonstrate that the theory or model is descriptively accurate or, where
that demonstration cannot be made, that the theory/model is robust with
respect to the specifications that cannot be validated.

As Rosaria said, simulation and theory should not be confused.  The
virtue of agent based simulation is that the agents can be descriptors
of observed behaviour.  Where different observers of behaviour have
different descriptions of that behaviour, then those different
descriptions can be modelled using agents.  Personally, I find it easier
to do that in declarative languages, but there is no insuperable
difficult about doing it in Java or C/C++ (hence, RePast or Swarm).

This is what makes agent based social simulation different from the long
line of empirically failed social theories and modelling techniques such
as  utility theory and game theory.  It enables us to engage with
observation and evidence without the constraints of unvalidated theory.
If good social science and social theory can be produced, then the
experience of the natural sciences is that it will be produced on the
basis of good observation and evidence.  Agent based modelling enables
us to formalise such observations without spurious generalisation.  As
such, it might be a means of developing good social theory.  But I
wouldn't expect to see that theory any time soon.


Scott Moss
Professor of Social Simulation
Centre for Policy Modelling
Manchester